PhD Position in Advanced Techniques for Emergency Robotic Catheterization
Develop innovative robotic catheterization systems to improve emergency stroke intervention and reduce radiation exposure.
Best for:Best for engineering or computer science graduates with strong robotics, mechatronics, or control systems backgrounds seeking a biomedical PhD.
Overview
The Robot Assisted Surgery group at KU Leuven is offering a fully-funded four-year PhD position focused on creating advanced robotic catheterization technologies for emergency procedures such as acute stroke mechanical thrombectomy. The research involves integrating novel sensing, control, and multi-instrument coordination strategies to enable safe and precise navigation through complex vascular anatomy. The successful candidate will work within a dynamic, multidisciplinary research team closely linked with clinical partners at UZ Leuven. The role includes participating in the EU-linked EiC PROMPT project, performing clinical validations, and engaging in limited teaching assistant duties.
What you'll do
- Design and develop advanced robotic catheterization technologies incorporating novel sensing and control strategies.
- Implement multi-instrument coordination algorithms for navigating intricate vascular anatomy during emergency interventions.
- Verify and validate robotic developments in realistic settings and collaborate closely with clinical partners at UZ Leuven.
- Contribute to research deliverables associated with the EiC PROMPT project and participate in international collaborations.
- Assist with academic teaching and mentoring tasks capped at 10% of total working hours.
- Disseminate research findings through peer-reviewed publications and conference presentations.
Requirements
Degree required: Master's degree in engineering or computer science
Degree offered: PhD
Language: English; fluency required
Instruction: English
- Master's degree obtained with distinction or equivalent excellent academic results
- Background in mechatronics, robotics, control engineering, mechanical engineering, deep learning, or medical imaging
- Strong practical problem-solving skills
- Ability to work independently and think critically
- Effective team player capabilities
- Must meet the admission requirements for the PhD programme at the KU Leuven Arenberg Doctoral School
Funding & terms
How to apply
Deadline: 2026-10-30
Candidates should submit their application online through the KU Leuven portal before the stated deadline. Ensure all required academic records and supporting documents are attached.
- CV
- Master's degree transcripts
- Motivation letter
Contact
Mirza Awais Ahmad· Researcher
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